Every organization that collects delinquent debt is faced with many of the same challenges: collect as much as you can, do it at the lowest possible cost, and do so in a way that is the least intrusive as possible. It is rare for any debt collection organization to want to significantly expand their staffing. Often, the goal is to do more with the same, or possibly even more with less. That is why analytics is in such high demand. Analytics offers the opportunity to work smarter, not harder. Here are four key reasons to consider expanding your use of predictive and prescriptive analytics:
Lower the Cost of Collections. Your best collectors, if they are given productive cases will collect money. The key is to provide them with the right case at the right time. Predictive models can literally forecast which cases are most likely to pay, and therefore the cases assigned to your collectors will be more productive. Where the models predict the cases will be less productive, they can be sent to a collection agency or you can send them for alternative, lower cost treatments.
Enhanced Customer Service. Predictive models can also help you enhance customer service in several ways. Predictive models can allow you to give lower risk customers more time to self-cure. Where the model predicts that a customer will pay through light touches, then you can give them more time to pay. The tone of phone calls and letters can be less insistent, which will also result in fewer complaints. Studies have shown that people who feel that they got better customer service are more likely to be compliant in the future. For commercial clients, happy customers typically continue to shop with the same company. By de-prioritizing these low risk cases, your staff can now focus on cases that likely wouldn’t be collected without their interventions. This will also result in a lower cost of collection.
Continual Improvement. Analytics can help you improve your operations by measuring the effect of individual changes to your collection approach. Using a feedback technique called “test and learn” you can have, for example, 80% of your cases use the existing collection strategies, 10% of cases use one alternate strategy and 10% of cases use another alternate strategy. The analytics can then accurately measure the impact of the changes from each strategy because all other factors will be kept in sync. This approach can also be used to compare different timings for contacts, different letter messaging, different call campaigns, different payment agreements, etc. Virtually any change in strategy can be compared accurately, rather than through hypothesis. This will allow you to continually improve your operations, or implement hybrid approaches where different debtors receive different treatments, because the alternate treatments produce maximum results for each debtor pool.
Optimize Overall Performance. Optimization, also known as Prescriptive Analytics, takes predictive analytics further by looking across an entire business process to find the single strategy or group of strategies that will result in the highest level of overall performance. The goals can be simple (maximize dollars collected) or complex (maximize dollars, while over-performing on a specific workload, and minimizing specific actions). The optimization algorithms can also account for staff, budget, legal and other constraints.
Prescriptive analytics also allows you to balance staff for each workload. The analytics could show opportunities if staff were moved between specific workloads, or specific activities on cases. It could show when to stop working a case, or where you have too many or two few resources working specific workloads. Prescriptive Analytics, like the Predictive Analytics also can utilize a “learning loop” where the results of your models are fed back into the model, allowing for continual automated tuning of your models. Where customer behaviors or economic changes have occurred, the models re-calibrate themselves to stay current over time.
It is also important to note that these analytics do not replace your own staff expertise, but rather they enhance your expertise. The analytics allow you calculate options mathematically and provide you with an objective, mathematical framework for making objective decisions and achieving a higher level of performance.